Analytics Engineer

Slate Magazine is looking for an analytics engineer to join our research and data team in our D.C. office. The research and data team works to help Slate understand traffic patterns, grow revenue from advertisements and subscriptions, and manage and productize its data.

We are looking for a candidate with the right mix of data analysis, data engineering, and visualization skills to help us build analytics products and infrastructure to drive Slate forward, further democratize data within the organization, and help us navigate the ever-changing world of ad technology. While technical knowledge and experience are important, the ideal candidate for this position will be a curious, critical thinker with a love for problem solving.

Key Responsibilities:

The analytics engineer reports to the director of research and data and will be primarily responsible for the following:

• Own Slate’s data infrastructure and ETL processes. On the technical side, this will mean experience writing SQL and Python and a good understanding of database systems.More importantly, we’re looking for someone who can think strategically about what our infrastructure should be going into the future.• Inform the larger product team on how we can incorporate existing external products or build custom tech to solve business problems, and work to push new analytics products through the MVP process•Manage existing data visualization tools and design and build new ones to help editorial, sales, and product teams answer analytics questions• Collect feedback on analytics tools, products, and services, and work to incorporate it into new iterations of our product stack

Required Qualifications:

• You have demonstrated experience combining, standardizing, and telling a story from data sets that are large, complicated, and often hard to relate• Prior experience in one or more of: managing ETL processes, database management, or sourcing data from APIs• Intermediate or better proficiency in one or more of the following: SQL (preferably in Redshift or a Postgres environment); Python for data manipulation (We currently use the luigi module.); Python or R for data analysis, command line tools and testing in a local environment; third-party data visualization tools like Looker, Tableau, Datorama, or Domo.• You’re comfortable working with nontechnical teams and with teams located in other cities across the country.

Nice-to-Have Qualifications:

• Prior experience working with advertiser data and with combining different revenue sources into a unified revenue model• Prior experience scoping and building MVPs and identifying how we can scale an MVP into a full product (functional prototypes)• Expertise in any of the above languages or tools• Experience at another publisher or experience managing data from websites• Experience with web-based optimization tools like Optimizely• Prior experience working with podcast data and advertisements• Prior experience working with membership programs like Slate Plus• Familiarity with Slate’s work!

Slateis committed to excellence through diversity, which involves attracting talented people from diverse backgrounds and traditions. We encourage everyone to apply.